Numerous methods to describe state variables have been used describe the “state” of a dynamic system. In simple thermodynamics systems, or mechanical systems, data and their derivatives are typical state variables; knowing these, the future behavior from objects in a system can be projected where the state and history describes enough about a system to determine its future. Sensor systems are subject to numerous conditions that have direct impacts on the state of their usefulness. One variable often used for sensor performance by definition is the Signal to Noise Ratio (SNR). Unfortunately SNR is often used to inappropriately describe sensor accuracy.
Therefore there is a need for better sensor performance, and while there are numerous methods to describe the state of sensor systems, extrapolation of sensor data to be used in a reliable business context remains a challenge.
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